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Azure HDInsight
Azure HDInsight

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Panoply

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Azure HDInsight vs Panoply: What are the differences?

Azure HDInsight: A cloud-based service from Microsoft for big data analytics. It is a cloud-based service from Microsoft for big data analytics that helps organizations process large amounts of streaming or historical data; Panoply: Collect, combine, and integrate all your data with any analytics tools. It is the data warehouse built for analysts. Our data management platform automates all three key aspects of the data stack: data collection, management, and query optimization.

Azure HDInsight and Panoply belong to "Big Data as a Service" category of the tech stack.

Some of the features offered by Azure HDInsight are:

  • Fully managed
  • Full-spectrum
  • Open-source analytics service in the cloud for enterprises

On the other hand, Panoply provides the following key features:

  • Data warehouse
  • Business Intelligence
  • Optimized Query Engine
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What is Azure HDInsight?

It is a cloud-based service from Microsoft for big data analytics that helps organizations process large amounts of streaming or historical data.

What is Panoply?

It is the data warehouse built for analysts. Our data management platform automates all three key aspects of the data stack: data collection, management, and query optimization.
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            What are some alternatives to Azure HDInsight and Panoply?
            Amazon EMR
            It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.
            Azure Databricks
            Accelerate big data analytics and artificial intelligence (AI) solutions with Azure Databricks, a fast, easy and collaborative Apache Spark–based analytics service.
            Apache Spark
            Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
            Amazon Redshift
            It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
            Google BigQuery
            Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.
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